Make Machine Learning Work in the Real World e-Book

€13+
5 ratings

I wrote a small ebook about applying validation techniques to different types of real-world datasets. Going into short examples of how different data types have to be treated to avoid overfitting.

I touch on the topics of:

  • overfitting
  • train-test splits
  • cross-validation
  • stratification
  • spatial validation
  • temporal validation
  • production
  • models data drift

This is a mini e-book as a reference guide for those that need quick insight to get an overview of the different pitfalls in real-worl machine learning.

I want this!

Mini e-book describing proper validation of machine learning models in real-world data regimes and how to keep them working in production settings.

Mini e-book
1
Size
28.3 MB
Length
19 pages

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€13+

Make Machine Learning Work in the Real World e-Book

5 ratings
I want this!